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Abstract:

An image processing apparatus includes: an isolated point detecting unit
that detects isolated points in image data; a line-shaped region
extracting unit that extracts line-shaped regions in the image data, as
character line candidate regions; an isolated point type determining unit
that determines a representative pixel of each isolated point in each
line-shaped region to be a pixel of interest, determines discontinuity of
each line-shaped region around the pixel of interest for each isolated
point, determines an isolated point determined to have discontinuity to
be a true isolated point, and determines an isolated point determined to
have no discontinuity to be a pseudo isolated point; and a halftone-dot
region determining unit that determines a halftone-dot region, based on
isolated point type determination results for the respective isolated
points detected by the isolated point detecting unit.

Claims:

1. An image processing apparatus comprising: an isolated point detecting
unit that detects isolated points in image data; a line-shaped region
extracting unit that extracts line-shaped regions in the image data, as
character line candidate regions; an isolated point type determining unit
that determines a representative pixel of each isolated point in each
line-shaped region to be a pixel of interest, determines discontinuity of
each line-shaped region around the pixel of interest for each isolated
point, determines an isolated point determined to have discontinuity to
be a true isolated point, and determines an isolated point determined to
have no discontinuity to be a pseudo isolated point; and a halftone-dot
region determining unit that determines a halftone-dot region, based on
isolated point type determination results for the respective isolated
points detected by the isolated point detecting unit.

2. The image processing apparatus according to claim 1, wherein when, in
a specific range around the pixel of interest, discontinuity of a
line-shaped region is detected on both sides of the pixel of interest in
a first direction and discontinuity of the line-shaped region is detected
on both sides of the pixel of interest in a second direction
perpendicular to the first direction, the isolated point type determining
unit determines an isolated point associated with the pixel of interest
to be a true isolated point.

3. The image processing apparatus according to claim 2, wherein when, in
the specific range around the pixel of interest, discontinuity of the
line-shaped region is detected on both sides of the pixel of interest in
a third direction and discontinuity of the line-shaped region is detected
on both sides of the pixel of interest in a fourth direction
perpendicular to the third direction, the isolated point type determining
unit determines an isolated point associated with the pixel of interest
to be a true isolated point, the third direction being different from the
first direction and the second direction.

4. The image processing apparatus according to claim 1, wherein the
isolated point type determining unit determines an isolated point
associated with the pixel of interest to be a true isolated point on
condition that, in a specific range around the pixel of interest,
discontinuity of a line-shaped region is detected on both sides of the
pixel of interest in at least one of a plurality of different directions.

5. The image processing apparatus according to claim 1, wherein the
halftone-dot region determining unit determines a region to be a
halftone-dot region, the region not including a pseudo isolated point but
including a true isolated point among the isolated points detected by the
isolated point detecting unit.

6. The image processing apparatus according to claim 1, wherein the
isolated point detecting unit detects, based on the image data, an
isolated point having a smaller grayscale value than surrounding pixels
thereof, as a black isolated point, the line-shaped region extracting
unit detects, based on the image data, a line-shaped region having a
smaller grayscale value than surrounding pixels thereof, as a positive
type line-shaped region, and the isolated point type determining unit
determines a representative pixel of each black isolated point in each
positive type line-shaped region to be a pixel of interest, determines
discontinuity of the positive type line-shaped region around the pixel of
interest for each black isolated point, determines a black isolated point
determined to have discontinuity to be a true isolated point, and
determines a black isolated point determined to have no discontinuity to
be a pseudo isolated point.

7. The image processing apparatus according to claim 1, wherein the
isolated point detecting unit detects, based on the image data, an
isolated point having a larger grayscale value than surrounding pixels
thereof, as a white isolated point, the line-shaped region extracting
unit detects, based on the image data, a line-shaped region having a
larger grayscale value than surrounding pixels thereof, as a negative
type line-shaped region, and the isolated point type determining unit
determines a representative pixel of each white isolated point in each
negative type line-shaped region to be a pixel of interest, determines
discontinuity of the negative type line-shaped region around the pixel of
interest for each white isolated point, determines a white isolated point
determined to have discontinuity to be a true isolated point, and
determines a white isolated point determined to have no discontinuity to
be a pseudo isolated point.

8. The image processing apparatus according to claim 1, wherein the
isolated point detecting unit: detects, based on the image data, an
isolated point having a smaller grayscale value than surrounding pixels
thereof, as a black isolated point; and detects, based on the image data,
an isolated point having a larger grayscale value than surrounding pixels
thereof, as a white isolated point, the line-shaped region extracting
unit: detects, based on the image data, a line-shaped region having a
smaller grayscale value than surrounding pixels thereof, as a positive
type line-shaped region; and detects, based on the image data, a
line-shaped region having a larger grayscale value than surrounding
pixels thereof, as a negative type line-shaped region, the isolated point
type determining unit: determines a representative pixel of each black
isolated point in each positive type line-shaped region to be a pixel of
interest, determines discontinuity of the positive type line-shaped
region around the pixel of interest for each black isolated point,
determines a black isolated point determined to have discontinuity to be
a true black isolated point, and determines a black isolated point
determined to have no discontinuity to be a pseudo black isolated point;
and determines a representative pixel of each white isolated point in
each negative type line-shaped region to be a pixel of interest,
determines discontinuity of the negative type line-shaped region around
the pixel of interest for each white isolated point, determines a white
isolated point determined to have discontinuity to be a true white
isolated point, and determines a white isolated point determined to have
no discontinuity to be a pseudo white isolated point, and the
halftone-dot region determining unit determines an OR region of a first
region and a second region to be a halftone-dot region, the first region
not including the pseudo black isolated point but including the true
black isolated point among black isolated points detected by the isolated
point detecting unit, and the second region not including the pseudo
white isolated point but including the true white isolated point among
the white isolated points detected by the isolated point detecting unit.

9. A non-transitory computer-readable recording medium having recorded
therein a program for causing a computer to perform the steps of: (a)
detecting isolated points in image data; (b) extracting line-shaped
regions in the image data, as character line candidate regions; (c)
determining a representative pixel of each isolated point in each
line-shaped region to be a pixel of interest, determining discontinuity
of each line-shaped region around the pixel of interest for each isolated
point, determining an isolated point determined to have discontinuity to
be a true isolated point, and determining an isolated point determined to
have no discontinuity to be a pseudo isolated point; and (d) determining
a halftone-dot region, based on isolated point type determination results
obtained in the step (c) for the respective isolated points detected in
the step (a).

Description:

[0001] This application is based on Japanese Patent Application No.
2011-000057 filed on Jan. 4, 2011, the contents of which are hereby
incorporated by reference.

BACKGROUND OF THE INVENTION

[0002] 1. Field of the Invention

[0003] The present invention relates to an image processing apparatus and
a technique related thereto.

[0004] 2. Description of the Background Art

[0005] In an image forming apparatus that forms an image based on a
scanned image, etc., a plurality of types of regions such as character
regions and halftone-dot regions are distinguished from each other and
each region is subjected to image processing, according to the type
thereof (see Japanese Patent Application Laid-Open No. 2002-218235). For
example, a smoothing process is performed on halftone-dot regions,
thereby suppressing the occurrence of moire, etc.

[0006] Note that Japanese Patent Application Laid-Open No. 2002-218235
describes detection of halftone-dot regions by an isolated point
detection process.

[0007] However, as will be described later, when halftone-dot regions are
determined only by an isolated point detection process, dots inside a
character (pixels representing the lines of the character) are also
extracted as pixels in a halftone-dot region. Then, if a smoothing
process is performed on the halftone-dot region in terms of the
prevention of moire, etc., then a problem of a blurred character edge
occurs.

SUMMARY OF THE INVENTION

[0008] An object of the present invention is to provide an image
processing technique capable of more appropriately extracting
halftone-dot regions from an image containing both characters and
halftone dots.

[0009] A first aspect of the present invention is directed to an image
processing apparatus including: an isolated point detecting unit that
detects isolated points in image data; a line-shaped region extracting
unit that extracts line-shaped regions in the image data, as character
line candidate regions; an isolated point type determining unit that
determines a representative pixel of each isolated point in each
line-shaped region to be a pixel of interest, determines discontinuity of
each line-shaped region around the pixel of interest for each isolated
point, determines an isolated point determined to have discontinuity to
be a true isolated point, and determines an isolated point determined to
have no discontinuity to be a pseudo isolated point; and a halftone-dot
region determining unit that determines a halftone-dot region, based on
isolated point type determination results for the respective isolated
points detected by the isolated point detecting unit.

[0010] A second aspect of the present invention is directed to a
non-transitory computer-readable recording medium having recorded therein
a program for causing a computer to perform the steps of (a) detecting
isolated points in image data; (b) extracting line-shaped regions in the
image data, as character line candidate regions; (c) determining a
representative pixel of each isolated point in each line-shaped region to
be a pixel of interest, determining discontinuity of each line-shaped
region around the pixel of interest for each isolated point, determining
an isolated point determined to have discontinuity to be a true isolated
point, and determining an isolated point determined to have no
discontinuity to be a pseudo isolated point; and (d) determining a
halftone-dot region, based on isolated point type determination results
obtained in the step (c) for the respective isolated points detected in
the step (a).

[0011] These and other objects, features, aspects and advantages of the
present invention will become more apparent from the following detailed
description of the present invention when taken in conjunction with the
accompanying drawings.

[0040] FIG. 29 is a diagram showing true isolated points, etc., obtained
by another isolated point determination operation; and

[0041] FIG. 30 is a diagram showing an image processing apparatus
according to a variant, etc.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0042] An embodiment of the present invention will be described below with
reference to the drawings.

[0043] <1. Configuration>

[0044] FIG. 1 is a schematic diagram showing an image processing apparatus
1 (1A). Here, the case in which the image processing apparatus 1 (1A) is
configured as a multifunction peripheral (also abbreviated as MFP) is
exemplified.

[0045] The MFP 1 is an apparatus having a scanner function, a printer
function, a copy function, a facsimile function, etc. (also referred to
as a multifunction product). Specifically, the MFP 1 includes an image
reading unit 2, a printout unit 4, a communication unit 5, an
input-output unit 6, a storage unit 8, and a controller 9. By allowing
these units to operate in an integrated manner, the above-described
functions are implemented.

[0046] The image reading unit 2 is a processing unit that optically reads
a document placed in a predetermined position of the MFP 1 and thereby
creates an image of the document (also referred to as a document image or
a scanned image). The image reading unit 2 is also referred to as a
scanner unit.

[0047] The printout unit 4 is an output unit that prints out an image on
various types of media such as paper, based on image data on a target
image.

[0048] The communication unit 5 is a processing unit capable of performing
facsimile communication via a public telephone line, etc. Also, the
communication unit 5 can perform network communication over a
communication network. By using the network communication, the MFP 1 can
give and receive various data to/from a desired target. In addition, by
using the network communication, the MFP 1 can send and receive emails.

[0049] The input-output unit 6 includes an operation input unit 61 that
accepts input to the MFP 1; and a display unit 62 that performs display
output of various types of information.

[0050] The storage unit 8 is composed of a storage apparatus such as a
hard disk drive (HDD). The storage unit 8 stores a document image, etc.,
created by the image reading unit 2, etc.

[0051] The controller 9 is a control apparatus that performs overall
control of the MFP 1, and is configured to include a CPU and various
semiconductor memories (a RAM, a ROM, and the like). Various functions of
the MFP 1 are implemented by various processing units operating under
control of the controller 9.

[0052] FIG. 2 is a diagram showing a functional block of the controller 9.
As shown in FIG. 2, the controller 9 includes a processing target image
creating unit 21, an isolated point detecting unit 23, a line-shaped
region extracting unit 24, an isolated point type determining unit 25, a
character line region determining unit 26, a halftone-dot region
determining unit 27, and a modified image creating unit 28.

[0053] The processing target image creating unit 21 is a processing unit
that creates, based on a scanned image, images for a region type
determination process (also referred to as images for region type
determination) for various regions (including halftone-dot regions,
character line regions, and the like).

[0054] The isolated point detecting unit 23 is a processing unit that
detects "isolated points" (described later) by performing an isolated
point detection process on the scanned image (specifically, the
above-described images for region type determination).

[0055] The line-shaped region extracting unit 24 is a processing unit that
extracts pixels in a "line-shaped region" (described later) by performing
an edge extraction process, etc., on the scanned image (specifically, the
above-described images for region type determination).

[0056] The isolated point type determining unit 25 is a processing unit
that determines the type of each isolated point detected by the isolated
point detecting unit 23. The isolated point type determining unit 25
determines, as will be described later, whether each isolated point is a
"true isolated point" or a "pseudo isolated point".

[0057] The character line region determining unit 26 is a processing unit
that determines character line regions in the scanned image, based on the
extraction results (line-shaped region extraction results) obtained by
the line-shaped region extracting unit 24 and the determination results
(isolated point type determination results) obtained by the isolated
point type determining unit 25.

[0058] The halftone-dot region determining unit 27 is a processing unit
that determines halftone-dot regions in the scanned image, based on the
detection results (isolated point detection results) obtained by the
isolated point detecting unit 23 and the determination results (isolated
point type determination results) obtained by the isolated point type
determining unit 25.

[0059] The modified image creating unit 28 is a processing unit that
creates a modified image in which appropriate image processing is
performed on the character line regions and the halftone-dot regions
which are determined by the character line region determining unit 26 and
the halftone-dot region determining unit 27.

[0060] Various types of image processing are performed on the scanned
image by the processing units 21 and 23 to 28, whereby a modified image
is created. Then, the modified image is printed out by the printout unit
4, whereby a so-called copy function, etc., are implemented.

[0061] <2. Image Processing>

[0062] Next, image processing, etc., performed by the processing units 21
and 23 to 28 will be described.

[0063] FIGS. 3 to 5 are flowcharts showing operations related to the image
processing, etc. FIG. 3 is a diagram showing main operations and FIG. 4
is a diagram showing a part of FIG. 3 (region determination process) in
detail. FIG. 5 is a diagram showing a part of FIG. 4 in more detail.

[0064] As shown in FIG. 3, in step S10, a region determination process is
performed. By the region determination process, a region in a scanned
image is divided into a plurality of types of regions (character line
regions, halftone-dot regions, and the like). Specifically, as will be
described later, the operation of determining the types of regions is
performed using detection results concerning "line-shaped regions" and
"isolated points" for the scanned image.

[0065] In step S50, the modified image creating unit 28 creates a modified
image in which appropriate image correction processes according to the
types of the respective regions are performed on the character line
regions and the halftone-dot regions which are determined by the
character line region determining unit 26 and the halftone-dot region
determining unit 27, respectively. For example, a smoothing process is
performed on the halftone-dot regions and an edge enhancement process is
performed on the character line regions, whereby the modified image is
created.

[0067] FIG. 4 is a diagram showing detailed operations of the region
determination process (step S10). With reference to FIG. 4, the region
determination process will be described in detail.

[0068] In steps S11 to S15, the operation of determining the type of a
region is performed using detection results concerning "positive type
line-shaped regions" (described later) and "black isolated points"
(isolated points each having a smaller grayscale value than its
surrounding pixels (surrounding region)) in a scanned image. In addition,
in parallel with the processes in steps S11 to S15, the processes in
steps S21 to S25 are performed. In steps S21 to S25, the operation of
determining the type of a region is performed using detection results
concerning "negative type line-shaped regions" (described later) and
"white isolated points" (isolated points each having a larger grayscale
value than its surrounding pixels (surrounding region)) in the scanned
image. In steps S31 and S32, the operations of finally determining the
types of regions are performed using the determination results obtained
in steps S11 to S15 and the determination results obtained in steps S21
to S25.

[0069] Note that prior to these processes, a min (R, G) image, a max (R,
G, B) image, an R-plane image, a G-plane image, etc., are created as
images for region type determination, based on the scanned image. Here,
the min (R, G) image is an image obtained after conversion of the
original full color image (scanned image) and is a grayscale image
obtained by converting a minimum value between the R component value and
G component value of each of the pixels forming the original full color
image, into a new pixel value (grayscale value) of the pixel. Likewise,
the max (R, G, B) image is an image obtained after conversion of the
original full color image and is a grayscale image obtained by converting
a maximum value among the R component value, G component value, and B
component value of each of the pixels forming the original full color
image, into a new pixel value of the pixel.

[0070] In this embodiment, as line-shaped regions (line-shaped regions
forming the lines of a character, etc.), two types of regions, a positive
type line-shaped region and a negative type line-shaped region, are
detected. Specifically, a positive type line-shaped region is detected
based on the min (R, G) image, and a negative type line-shaped region is
detected based on the max (R, G, B) image. The positive type line-shaped
region is a line-shaped region with a relatively dark color relative to a
background color, and the negative type line-shaped region is a
line-shaped region with a relatively light color relative to a background
color. The positive type line-shaped region is also represented as a
line-shaped region with a relatively low luminance relative to the
background, and the negative type line-shaped region as a line-shaped
region with a relatively high luminance relative to the background.

[0071] In addition, in this embodiment, based on the R-plane image, "black
isolated points" are detected and "white isolated points" are also
detected. Likewise, based on the G-plane image, "black isolated points"
are detected and "white isolated points" are also detected. Note that
here the B-plane image is not used for the process of detecting "black
isolated points" and "white isolated points". Note, however, that the
configuration is not limited thereto and the B-plane image may also be
used for the process of detecting "black isolated points" and/or "white
isolated points".

[0072] FIGS. 6 to 9 each are a diagram showing an example of a scanned
image (a part). FIG. 6 is a diagram showing a scanned image which is a
color image (note, however, that in the drawing the scanned image is
shown in grayscale). FIG. 6 shows a state in which the red characters
"SAMPLE" are depicted with cyan halftone-dot regions being a background.
FIGS. 7 to 9 are diagrams respectively showing three primary color planes
(an R-plane, a G-plane, and a B-plane) of the scanned image. FIG. 7 is a
diagram showing an R-plane, FIG. 8 is a diagram showing a G-plane, and
FIG. 9 is a diagram showing a B-plane. FIG. 10 is a diagram showing the
processing results of an isolated point detection process in step S11,
and FIG. 11 is a diagram showing the processing results of a line-shaped
region extraction process in step S12. Note that here a situation is
assumed in which the red color of the characters "SAMPLE" is detected
slightly deviated from the ideal red color. For example, the red color of
the characters "SAMPLE" is a color represented by (R, G, B)=(220, 30,
50).

[0073] FIG. 12 is an enlarged view showing a halftone-dot region RD in the
scanned image, and FIG. 13 is an enlarged view showing portions in the
vicinity of a character line region RL in the scanned image. FIG. 12
shows a cyan halftone-dot region RD. In FIG. 13, a red character (here,
"L") is superimposed on a part of the cyan halftone-dot region RD. In
these drawings, each halftone dot is shown as a square having a
predetermined size (e.g., 3 pixels×3 pixels). Note that for
simplicity's sake, figures subsequent to FIG. 12 show halftone dots
having a different angle than halftone dots in FIGS. 6 to 11.

[0074] First, in step S11 (FIG. 4), the isolated point detecting unit 23
performs an isolated point detection process on an image created based on
a scanned image (here, first, the R-plane image (FIG. 7)) and thereby
detects isolated points (specifically, black isolated points). A "black
isolated point" is an isolated point having a smaller grayscale value
than its surrounding pixels. In short, a black isolated point is a black
dot isolated from its surrounding.

[0075] In the isolated point detection process, the sizes and positions of
the isolated points are detected.

[0076] For example, an isolated point (black isolated point) of the
isolated point size "1" is detected by a process such as that shown
below. Specifically, as shown in FIG. 23, a pixel value V5 of a pixel of
interest P5 is compared with a minimum value min (P1 to P3, P4, P6, and
P7 to P9) among the pixel values of a plurality of its surrounding pixels
P1 to P3, P4, P6, and P7 to P9. Specifically, when a condition is
established where the pixel value V5 is smaller than the minimum value
min (P1 to P3, P4, P6, and P7 to P9), it is detected that the pixel of
interest P5 is a "black isolated point". In other words, a black isolated
point with the position of the pixel of interest P5 being the position of
the barycenter is detected. As described above, the size of this black
isolated point (isolated point size) is "1 (pixel)".

[0077] Likewise, an isolated point of the isolated point size "3" is
detected by a process such as that shown below. Specifically, as shown in
FIG. 24, a pixel value V33 of a pixel of interest P33 is compared with
the pixel values of a plurality of its surrounding pixels P11 to P15, P21
to P25, P31, P32, P34, P35, P41 to P45, and P51 to P55. For example, when
conditions are established where the pixel value V33 is smaller than a
minimum value mini of its surrounding pixels (P22 to P24, P32, P34, and
P42 to P44) and the minimum value mini is smaller than a minimum value
mint of further outer surrounding pixels (P11 to P15, P21, P25, P31, P35,
P41, P45, and P51 to P55), it is detected that a pixel group of 3
pixels×3 pixels around the pixel of interest P33 is a "black
isolated point". In other words, a black isolated point with the position
of the pixel of interest P33 being the position of the barycenter is
detected. As described above, the size of this black isolated point
(isolated point size) is "3 (pixels)". Note that the position of the
barycenter of an "isolated point" is also represented as a representative
position of the "isolated point", etc. Note also that in addition to the
above-described conditions, when a condition is further established where
an average value ave1 of the surrounding pixels (P22 to P24, P32, P34,
and P42 to P44) is smaller than an average value ave2 of the further
outer surrounding pixels (P11 to P15, P21, P25, P31, P35, P41, P45, and
P51 to P55), it may be determined that the above-described pixel group of
3 pixels×3 pixels is a "black isolated point".

[0078] In a likewise manner, black isolated points of a plurality of other
sizes are detected. In this manner, the position of the barycenter
(representative position) of a black isolated point of each size, etc.,
are detected. Note that when one same pixel of interest EB is detected in
an overlapping manner as isolated points of a plurality of sizes, the
largest one of the detected isolated point sizes may be determined to be
the isolated point size of the pixel of interest EB.

[0079] By such a process, for example, as shown in FIGS. 10, 14, and 15, a
plurality of isolated points (specifically, black isolated points) are
detected. FIG. 14 shows isolated points (black isolated points) PS
extracted from the halftone-dot region RD in FIG. 12, and FIG. 15 shows
isolated points (black isolated points) PS extracted from the
halftone-dot region RD and the character line region RL in FIG. 13. In
FIGS. 14 and 15, each isolated point PS of a (3×3) pixel size is
shown as a dashed line square and a barycentric pixel PB of each isolated
point is shown as a black pixel at its center.

[0080] In the above-described manner, a black isolated point detection
process based on the R-plane image is performed. Cyan halftone dots are
particularly easily detected as black isolated points in the R-plane
image (a plane image of red which is a complementary color of cyan).

[0081] In a likewise manner, a black isolated point detection process
based on the G-plane image is also performed. Note that although the
G-plane image in FIG. 8 is shown such that there are no corresponding
dots present in halftone-dot regions, when, for example, "cyan" is
slightly deviated from the ideal cyan, black isolated points
corresponding to halftone dots are also detected in the G-plane image,
etc.

[0082] Note that in each color component plane, a plurality of dots
forming a halftone-dot region of its complementary color are easily
detected as isolated points. For example, as described above, in an
R-plane, halftone dots of cyan (C) which is a complementary color of red
(R) are easily detected as isolated points. Likewise, in a G-plane,
halftone dots of magenta (M) which is a complementary color of green (G)
are easily detected as isolated points. By using plane images of a
plurality of color components, halftone dots of various colors can be
favorably detected.

[0083] Thereafter, subsequent processes are performed using both of the
black isolated points detected based on the R-plane image and the black
isolated points detected based on the G-plane image. FIG. 10 shows both
of the black isolated points detected based on the R-plane image and the
black isolated points detected based on the G-plane image.

[0084] Here, as can be seen by referring to FIGS. 6 and 15, etc., isolated
points PS are also present inside the character line region (line
(including a dot, a straight line, and a curve)-shaped regions forming a
character (pixel group)) RL. Hence, as shown in FIG. 15, in particular,
isolated points (black isolated points) PS are detected not only in the
halftone-dot region but also inside the character line region (an
L-shaped region surrounded by a thick dashed line) RL.

[0085] If a region where those isolated points PS are present is
determined to be a halftone-dot region as it is, then a region including
the character line region RL is determined to be a halftone-dot region.
Then, as described above, if a smoothing process is performed on such a
halftone-dot region, then a smoothing process is also performed on the
character line region RL, which may cause a problem of a blurred
character edge.

[0086] In the embodiment, on the other hand, such a problem is solved by
performing processes at and subsequent to the next step S12.

[0087] Specifically, first, in step S12, line-shaped regions RE are
extracted from a scanned image (here, the min (R, G) image) by the
line-shaped region extracting unit 24. More specifically, an edge
extraction process is performed on the min (R, G) image, whereby edges of
a character, etc., are extracted. Then, closed regions surrounded by the
extracted edges are extracted as regions (line-shaped regions) formed of
the "lines" of a character, etc. The line-shaped regions RE are extracted
as candidate regions for lines forming a character (also referred to as
character line candidate regions). Note that the thickness of the
line-shaped regions RE is not limited to a one-pixel width and can have
various appropriate sizes. The shape of the line-shaped regions RE is,
for example, a dot, a straight line, a curve, or the like. A line-shaped
region RE here is a region having a smaller grayscale value than the
pixels in its outer region (surrounding region) and is a candidate region
for a line of a positive-state character (a character with a darker
(blacker) color than a background color), and thus is also represented as
a "positive type character line candidate region" or a "positive type
line-shaped region".

[0088] Accordingly, for example, as shown in FIGS. 11, 16, and 17,
line-shaped regions (line-shaped regions each including an edge and a
region inside the edge) RE are detected. FIG. 16 shows line-shaped
regions (positive type line-shaped regions) RE extracted from the
halftone-dot region in FIG. 12, and FIG. 17 shows line-shaped regions
(positive type line-shaped regions) RE (REp) extracted from the
halftone-dot region and the character line region in FIG. 13. In FIGS. 16
and 17, the extracted line-shaped regions are shown in black. Note that a
line-shaped region here is a region including a detected edge and a
region inside the edge and thus is also referred to as an "edge's inside
region" (positive type edge's inside region), etc.

[0089] FIG. 18 is a diagram showing the isolated point detection results
(FIG. 14) and the line-shaped region extraction results (FIG. 16) in a
superimposed manner, and FIG. 19 is a diagram showing the isolated point
detection results (FIG. 15) and the line-shaped region extraction results
(FIG. 17) in a superimposed manner. Note that, in FIGS. 18 and 19, the
isolated point detection results are shown such that the barycentric
pixels of the detected isolated points are shown in black, and the
line-shaped region extraction results are shown such that the extracted
line-shaped regions are shown in light color.

[0090] FIGS. 20 to 22 each are a diagram showing an example of the scanned
image, etc., in more detail. FIG. 20 is a diagram showing a cyan
halftone-dot region in the scanned image. FIG. 21 is a diagram showing
the results of detection of black isolated points PSp and the results of
extraction of positive type line-shaped regions REp, for the halftone-dot
region in FIG. 20. In FIG. 21, a non-white, light colored pixel
represents a pixel in a positive type line-shaped region REp, and a dark
colored pixel represents a barycentric pixel PBp of a black isolated
point PSp. A white pixel represents a pixel that is neither a pixel
inside a positive type line-shaped region nor a pixel of a black isolated
point. FIG. 22 is a diagram showing the results of detection of white
isolated points PSn and the results of extraction of negative type
line-shaped regions REn, for the halftone-dot region in FIG. 20. In FIG.
22, a light colored pixel represents a pixel in a negative type
line-shaped region REn, and a dark colored pixel represents a barycentric
pixel PBn of a white isolated point PSn. A white pixel represents a pixel
that is neither a pixel in a negative type line-shaped region nor a pixel
of a white isolated point. Note that a "white isolated point" and a
"negative type line-shaped region" will be described later.

[0091] Here, in the line-shaped region extraction process, an original
character line region RL is extracted as a line-shaped region RE and the
above-described isolated points PS are also extracted as line-shaped
regions RE. For example, in FIG. 17 a character line region RL for the
character "L" is extracted as a line-shaped region RE, and isolated
points PS around the character "L" are also extracted as line-shaped
regions RE. In addition, each isolated point PS in FIG. 16 is also
extracted as a line-shaped region RE. Therefore, it is difficult to
accurately extract a character line region by using only the results of
the line-shaped region extraction process.

[0092] On the other hand, in the embodiment, processes at and subsequent
to the next step S13 are further performed.

[0093] In step S13, the types of a plurality of isolated points
(specifically, black isolated points) detected in step S11 are determined
by the isolated point type determining unit 25. Specifically, the
isolated point type determining unit 25 determines whether each isolated
point is a "true isolated point" or a "pseudo isolated point".

[0094] Here, a "pseudo isolated point" is one of a plurality of isolated
points (see FIG. 10, etc.) detected from the inside the character line
region by the isolated point detection process in step S11 and is
detected as an isolated point by erroneous detection despite the fact
that it is not an isolated point in the original meaning. Here, such an
isolated point is also referred to as a "pseudo isolated point" in order
to show that the isolated point is not an original isolated point. On the
other hand, an original isolated point is also referred to as a "true
isolated point". Accordingly, two types of isolated points are
distinguished from each other.

[0095] The isolated point type determining unit 25 determines a pixel that
is present in a line-shaped region RE and that is also a representative
pixel (barycentric pixel) PB of an isolated point PS, to be a pixel of
interest EB, and determines discontinuity of the line-shaped region RE
around the pixel of interest EB. In other words, the isolated point type
determining unit 25 determines discontinuity of each line-shaped region
for each isolated point. An isolated point that is an isolated point PS
associated with a pixel of interest EB and that is determined to have
discontinuity regarding a line-shaped region RE is determined to be a
"true isolated point". On the other hand, an isolated point that is an
isolated point PS associated with a pixel of interest EB and that is
determined to have no discontinuity regarding a line-shaped region RE is
determined to be a "pseudo isolated point".

[0096] Specifically, as shown in FIG. 5, first, in step S41, a pixel of
interest EB is selected. In step S41, a pixel that is present in a
line-shaped region and that is a representative pixel (barycentric pixel)
of an isolated point is determined to be a pixel of interest EB. For
example, a pixel EB1, etc., such as those shown in FIG. 25 are determined
to be pixels of interest EB.

[0097] Then, in step S42, the size of a detection target region is
determined based on the isolated point size of the isolated point PS
associated with the pixel of interest EB. For example, the range of a
predetermined number of pixels with the pixel of interest EB being at the
center (e.g., an isolated point size N of the pixel of interest EB) is
determined to be a detection target region TD (see FIG. 25).

[0098] Then, in step S43, the isolated point type determining unit 25
determines discontinuity of the line-shaped region around the pixel of
interest EB, in four directions DR1 to DR4 (see FIGS. 25 and 26).

[0099] The isolated point type determining unit 25 first determines
whether discontinuity of the line-shaped region RE is detected on both
sides of the pixel of interest EB in the first direction DR1 (e.g., a
direction having an inclination of 0 degrees with respect to an X-axis).
The discontinuity detection is performed on the detection target region
TD determined in step S42.

[0100] Specifically, when the pixel of interest EB is an isolated point of
the isolated point size "3" (N=3), a determination as to whether
discontinuity of a line-shaped region is detected on "both sides" of the
pixel of interest EB in the first direction DR1 is made as follows. More
specifically, it is determined whether to satisfy conditions where, in
the direction DR1 (X direction), there is a pixel not in a line-shaped
region RE within the range of from the pixel of interest EB to the third
pixel on the left side (-X side) from the pixel of interest EB (the range
including pixels at both ends) and there is a pixel not in a line-shaped
region RE within the range of from the pixel of interest EB to the third
pixel on the right side (+X side) from the pixel of interest EB (the
range including pixels at both ends). In short, it is determined whether
there are pixels in "non-line-shaped regions" in both directions, the
left and right directions, starting from the pixel of interest EB. When
the conditions are satisfied, it is determined that discontinuity of the
line-shaped region RE is detected on "both sides" of the pixel of
interest EB in the first direction DR1. On the other hand, when the
conditions are not satisfied, it is not determined that discontinuity of
the line-shaped region RE is detected on "both sides" of the pixel of
interest EB in the first direction DR1.

[0101] For example, for the pixel of interest EB1 in FIG. 25, in the first
direction DR1 (see also FIG. 26), there are pixels not in line-shaped
regions RE (outside pixels (white pixels in the drawings)) in the
position of the second pixel on the right side from the pixel of interest
EB1 and in the position of the second pixel on the left side from the
pixel of interest EB1. Therefore, it is determined that discontinuity of
a line-shaped region RE is detected on "both sides" of the pixel of
interest EB1 in the first direction DR1.

[0102] On the other hand, for a pixel of interest EB2 in FIG. 25, in both
of the first direction DR1 and the second direction DR2, there are no
pixels not in line-shaped regions RE in a detection target region TD
(pixels are all present in line-shaped regions RE) and thus it is not
determined that discontinuity of a line-shaped region RE is detected. For
a pixel of interest EB3 in FIG. 25, in the first direction DR1, there is
a pixel not in a line-shaped region RE (a white region surrounded by a
thin dashed line in FIG. 25) on the left side of the pixel of interest
EB3 in a detection target region TD, but there is no pixel not in a
line-shaped region RE on the right side of the pixel of interest EB3 in
the detection target region TD. In other words, there is no discontinuity
of a line-shaped region RE on the right side of the pixel of interest
EB3. Therefore, it is not determined that discontinuity of the
line-shaped region RE is detected on "both sides" of the pixel of
interest EB3 in the first direction DR1.

[0103] For a pixel of interest EB associated with an isolated point of a
size other than the isolated point size "3", too, likewise, the same
determination process as that described above is performed in a specific
range (the range of a predetermined number of pixels) TD around the pixel
of interest EB (specifically, in a detection target region TD according
to the isolated point size).

[0104] Then, the isolated point type determining unit 25 next determines
in a likewise manner whether discontinuity of the line-shaped region RE
is detected on both sides of the pixel of interest EB in the second
direction DR2 perpendicular to the first direction DR1 (e.g., a direction
having an inclination of 90 degrees with respect to the X-axis (i.e., a Y
direction)). For example, when, in the second direction DR2 (Y
direction), there is a pixel not in a line-shaped region RE within the
range of from the pixel of interest EB to an Nth pixel on the lower side
(-Y side) from the pixel of interest EB and there is a pixel not in a
line-shaped region RE within the range of from the pixel of interest EB
to an Nth pixel on the upper side (+Y side) from the pixel of interest
EB, it is determined that discontinuity of the line-shaped region RE is
detected on both sides of the pixel of interest EB in the second
direction DR2.

[0105] In addition, the isolated point type determining unit 25 next
determines in a likewise manner whether discontinuity of the line-shaped
region RE is detected on both sides of the pixel of interest EB in the
third direction DR3 (e.g., a direction having an inclination of +45
degrees with respect to the X-axis). For example, when, in the third
direction DR3, there is a pixel not in a line-shaped region RE within the
range of from the pixel of interest EB to an Nth pixel on the lower left
side (-X side and -Y side) from the pixel of interest EB and there is a
pixel not in a line-shaped region RE within the range of from the pixel
of interest EB to an Nth pixel on the upper right side (+X side and +Y
side) from the pixel of interest EB, it is determined that discontinuity
of the line-shaped region RE is detected on both sides of the pixel of
interest EB in the third direction DR3.

[0106] Furthermore, the isolated point type determining unit 25 next
determines in a likewise manner whether discontinuity of the line-shaped
region RE is detected on both sides of the pixel of interest EB in the
fourth direction DR4 perpendicular to the third direction DR3 (e.g., a
direction having an inclination of 135 degrees (-45 degrees) with respect
to the X-axis). For example, when, in the fourth direction DR4, there is
a pixel not in a line-shaped region RE within the range of from the pixel
of interest EB to an Nth pixel on the upper left side (-X side and +Y
side) from the pixel of interest EB and there is a pixel not in a
line-shaped region RE within the range of from the pixel of interest EB
to an Nth pixel on the lower right side (+X side and -Y side) from the
pixel of interest EB, it is determined that discontinuity of the
line-shaped region RE is detected on both sides of the pixel of interest
EB in the fourth direction DR4.

[0107] Then, in step S44, the isolated point type determining unit 25
determines the type of the isolated point associated with the pixel of
interest EB, according to whether a predetermined criterion is satisfied.
Here, whether discontinuity of the line-shaped region RE is detected on
both sides of the pixel of interest EB in a set of two perpendicular
directions ((DR1 and DR2) or (DR3 and DR4)) among the four directions is
adopted as the predetermined criterion.

[0108] Specifically, when the isolated point type determining unit 25
determines that discontinuity of the line-shaped region RE is detected on
both sides of the pixel of interest EB in both of the two directions DR1
and DR2 in given two perpendicular directions (DR1 and DR2), the isolated
point type determining unit 25 determines that the isolated point
associated with the pixel of interest EB is a "true isolated point" (step
S45). Likewise, when the isolated point type determining unit 25
determines that discontinuity of the line-shaped region RE is detected on
both sides of the pixel of interest EB in both of the two directions DR3
and DR4 in the other two perpendicular directions (DR3 and DR4), too, the
isolated point type determining unit 25 determines that the isolated
point associated with the pixel of interest EB is a "true isolated point"
(step S45). Such determinations are made because when "disconnection" of
the line-shaped region RE on both sides of the pixel of interest EB is
present in both of the two perpendicular directions in the
above-described manner, the pixel of interest EB (specifically, the
isolated point associated with the pixel of interest EB) is highly likely
to be an "isolated point" (true isolated point) in the original meaning.

[0109] On the other hand, isolated points other than "true isolated
points" are determined to be "pseudo isolated points". Specifically, when
it is not determined that discontinuity of the line-shaped region RE is
detected on both sides of the pixel of interest EB in at least one of
given two perpendicular directions (DR1 and DR2) and it is not determined
that discontinuity of the line-shaped region RE is detected on both sides
of the pixel of interest EB in at least one of the other two
perpendicular directions (DR3 and DR4), the isolated point associated
with the pixel of interest EB is determined to be a "pseudo isolated
point" (step S46). Such a determination is made because when
"disconnection" of the line-shaped region RE on both sides of the pixel
of interest EB is not present in at least one of two perpendicular
directions in the above-described manner, the pixel of interest EB is
highly likely not to be an original isolated point.

[0110] For example, for the pixel of interest EB1 in FIG. 25,
discontinuity of a line-shaped region RE is detected on "both sides" of
the pixel of interest EB1 in the first direction DR1. In addition, for
the pixel of interest EB1, discontinuity of the line-shaped region RE is
detected on "both sides" of the pixel of interest EB1 in the second
direction DR2, too. In other words, for the pixel of interest EB1,
"discontinuity of the line-shaped region" is detected on both sides of
the pixel of interest EB1 in both of the first direction DR1 and the
second direction DR2. Therefore, an isolated point associated with the
pixel of interest EB1 is determined to be a "true isolated point".

[0111] On the other hand, for the pixel of interest EB2 in FIG. 25, in
both of the first direction DR1 and the second direction DR2, there are
no pixels not in line-shaped regions RE in a detection target region TD
and thus discontinuity of a line-shaped region RE is not detected.
Likewise, in both of the third direction DR3 and the fourth direction
DR4, too, there are no pixels not in line-shaped regions RE in the
detection target region TD and thus discontinuity of the line-shaped
region RE is not detected. Therefore, an isolated point associated with
the pixel of interest EB2 is determined to be a "pseudo isolated point".

[0112] For the pixel of interest EB3 in FIG. 25, there is no discontinuity
of a line-shaped region RE on the right side of the pixel of interest EB3
and thus it is not determined that discontinuity of the line-shaped
region RE is detected on "both sides" of the pixel of interest EB3 in the
first direction DR1. Note that in the second direction, too, it is not
determined that discontinuity of the line-shaped region RE is detected on
"both sides" of the pixel of interest EB3. Furthermore, in both of the
third direction DR3 and the fourth direction DR4, too, there are no
pixels not in line-shaped regions RE in a detection target region TD and
thus discontinuity of the line-shaped region RE is not detected.
Therefore, an isolated point associated with the pixel of interest EB3 is
determined to be a "pseudo isolated point" (pseudo black isolated point).

[0113] Here, in FIG. 25, etc., the case in which the halftone-dot angle is
45 degrees is mainly assumed. In this case, it is particularly useful to
determine, as described above, when discontinuity of a line-shaped region
RE is detected on both sides of a pixel of interest EB in both of the two
directions DR1 and DR2 perpendicular to each other, an isolated point
(black isolated point) associated with the pixel of interest EB to be a
"true isolated point" (true black isolated point) (step S45).

[0114] Note, however, that there is also a case in which the halftone-dot
angle is 0 degrees. In that case, it is particularly useful to determine,
when discontinuity of a line-shaped region RE is detected on both sides
of a pixel of interest EB in both of the two directions DR3 and DR4
perpendicular to each other, an isolated point associated with the pixel
of interest EB to be a "true isolated point" (step S45). In this case, as
shown in FIG. 27, since discontinuity of a line-shaped region RE for a
halftone dot is easily detected in the directions DR3 and DR4, a true
isolated point for such a halftone dot is easily and accurately detected.

[0115] Therefore, to more appropriately handle halftone dots with various
angles, it is preferable to perform, as described above, an isolated
point type determination operation using discontinuity not only for the
directions DR1 and DR2 but also for the directions DR3 and DR4.

[0116] In the next step S47, a process of removing pseudo isolated points
(pseudo black isolated points) from a plurality of isolated points (black
isolated points) detected in step S11 (FIG. 4), based on the isolated
point type determination results obtained in steps S44 to S46 is
performed (see FIG. 28).

[0117] Then, in step S48, it is determined whether the processes in steps
S41 to S46 have been done for all of the isolated points (black isolated
points) in the line-shaped regions RE. If there is a remaining undone
pixel, then processing returns to step S41. On the other hand, if it is
determined that the processes in steps S41 to S46 have been done for all
of the isolated points in the line-shaped regions RE, then the process in
step S13 is completed. In this manner, the processes in steps S41 to S46
are performed for all of the isolated points (black isolated points) in
the line-shaped regions RE.

[0118] By the processes such as those described above (steps S41 to S48),
all of the pseudo isolated points (pseudo black isolated points) are
removed from the isolated point detection results obtained in step S11.

[0119] As a result, ideally, of a plurality of isolated points detected in
step S11 (see FIG. 10), all of the pseudo isolated points present in the
character line regions RL for the characters "SAMPLE" are removed. FIG.
28 is a diagram showing isolated points (true isolated points), etc.,
after the removal of pseudo isolated points. For example, as can be seen
by comparing FIGS. 28 and 19, in FIG. 28, pseudo isolated points are
removed from a plurality of isolated points in FIG. 19. Specifically,
isolated points (pseudo black isolated points) are removed from a
substantially L-shaped line-shaped region RE in the center of the drawing
(a region including a character line region RL).

[0120] In the next step S14, a halftone-dot region determination process
based on the isolated point type determination results is performed.
Specifically, the halftone-dot region determining unit 27 determines a
region in which pseudo isolated points (pseudo black isolated points) are
removed from a plurality of isolated points (black isolated points) (in
other words, a region not including pseudo black isolated points but
including true black isolated points among a plurality of black isolated
points), to be a halftone-dot region. More specifically, the halftone-dot
region determining unit 27 performs a process of extending each isolated
point (black isolated point) to its adjacent isolated point and thereby
creates a continuous region including the isolated points (black isolated
points), and determines the continuous region to be a halftone-dot
region. For example, in FIG. 28, a region surrounded by a dash-dotted
line is determined to be a halftone-dot region.

[0121] In step S15, a line-shaped region determination process is
performed. Specifically, the character line region determining unit 26
determines a line-shaped region RE (positive type line-shaped region REp)
from which true isolated points (true black isolated points) are removed,
to be a character line region. More specifically, the character line
region determining unit 26 modifies a line-shaped region by excluding a
region obtained by extending each true isolated point (true black
isolated point) according to its isolated point size, from a line-shaped
region RE extracted in step S12. Then, the line-shaped region after the
exclusion (after the modification) is determined to be a character line
region. For example, in FIG. 28, an L-shaped region surrounded by a
dash-double-dotted line is determined to be a character line region.

[0122] In steps S21 to S25 (FIG. 4), too, the same operations as those in
steps S11 to S15 are performed. Note, however, that the operations are
different in that, for example, the positive and negative are reversed, a
"white isolated point" is adopted instead of a "black isolated point",
and a "negative type line-shaped region" is adopted instead of a
"positive type line-shaped region".

[0123] Specifically, first, in step S21, the isolated point detecting unit
23 performs an isolated point detection process on images (the R-plane
image, etc.) created based on the scanned image and thereby detects
isolated points (specifically, white isolated points). A "white isolated
point" is an isolated point having a larger grayscale value than its
surrounding pixels. In short, a "white isolated point" is a white dot
isolated from its surrounding.

[0124] Note that detection of a white isolated point differs from
detection of a black isolated point in that, for example, the large and
small of their grayscale values are reversed. For example, a white
isolated point of the isolated point size "1" is detected by a process
such as that shown below. Specifically, when a condition is established
where the pixel value V5 of a pixel of interest P5 (see FIG. 23) is
larger than the maximum value max of its surrounding pixels (P1 to P3,
P4, P6, and P7 to P9), it is detected that the pixel of interest P5 is a
"white isolated point". In other words, a white isolated point with the
position of the pixel of interest P5 being the position of the barycenter
is detected. Likewise, the operation of detecting white isolated points
of other sizes is also performed such that the large and small of their
grayscale values, etc., are reversed from those for the operation of
detecting black isolated points.

[0125] Then, in step S22, line-shaped regions RE are extracted from a
scanned image (here, the max (R, G, B) image) by the line-shaped region
extracting unit 24. Specifically, an edge extraction process is performed
on the max (R, G, B) image, whereby edges of a character, etc., are
extracted. Then, closed regions surrounded by the extracted edges are
extracted as line-shaped regions (character line candidate regions). Note
that a line-shaped region RE is a region having a larger grayscale value
than the pixels in its outer region (surrounding region) and is a
candidate region for a line of a negative-state character (a character
with a lighter (whiter) color than a background color), and thus is also
represented as a "negative type character line candidate region" or a
"negative type line-shaped region".

[0126] As a result, for example, as shown in FIG. 22, white isolated
points PS (PSn) for the halftone-dot region in FIG. 20 are detected by
the process in step S21 and negative type line-shaped regions RE (REn)
for the halftone-dot region in FIG. 20 are detected by the process in
step S22. Note that in FIG. 22, for the sake of expediency of depiction,
light and dark are shown reversed again and a relatively white portion in
a grayscale image is shown to be relatively black. Hence, a barycentric
pixel PB (PBn) of a white isolated point PS (PSn) is shown in dark color,
and a negative type line-shaped region RE (REn) which is originally white
or light colored is shown in darker color than the white color of its
outer region (non-negative type line-shaped region) (note, however, that
the negative type line-shaped region RE (REn) is shown in a lighter color
than that of the barycentric pixel PBn of the white isolated point PSn).

[0127] Then, in step S23, the types of a plurality of isolated points
(specifically, white isolated points) detected in step S21 are determined
by the isolated point type determining unit 25. The process in this step
S23 is the same as that in step S13.

[0128] Accordingly, it is determined whether each white isolated point is
a "true white isolated point" or a "pseudo white isolated point", and a
process of removing pseudo isolated points (pseudo white isolated points)
from a plurality of isolated points (white isolated points) detected in
step S21 is performed.

[0129] In the next step S24, a halftone-dot region determination process
based on the isolated point type determination results is performed.
Specifically, the halftone-dot region determining unit 27 determines a
region in which pseudo white isolated points are removed from a plurality
of white isolated points (in other words, a region not including pseudo
white isolated points but including true white isolated points among a
plurality of white isolated points), to be a halftone-dot region. More
specifically, the halftone-dot region determining unit 27 performs a
process of extending each white isolated point to its adjacent white
isolated point and thereby creates a continuous region including true
white isolated points, and determines the continuous region to be a
halftone-dot region.

[0130] Furthermore, in step S25, a line-shaped region determination
process is performed. Specifically, the character line region determining
unit 26 determines a negative type line-shaped region REn from which true
white isolated points are removed, to be a character line region. More
specifically, the character line region determining unit 26 modifies a
negative type line-shaped region by excluding a region obtained by
extending each true white isolated point according to its isolated point
size, from a negative type line-shaped region REn extracted in step S22.
Then, the negative type line-shaped region after the exclusion (after the
modification) is determined to be a character line region.

[0131] Thereafter, in step S31, the results of determinations in steps S14
and S24 are integrated. Specifically, two regions, a halftone-dot region
determined in step S14 by a combination of black isolated points PSp and
positive type line-shaped regions REp and a halftone-dot region
determined in step S24 by a combination of white isolated points PSn and
negative type line-shaped regions REn, (in other words, the OR region of
the two regions (union region)) are finally determined to be a
"halftone-dot region".

[0132] In addition, in step S32, the results of determinations in steps
S15 and S25 are integrated. Specifically, two regions, a character line
region determined in step S15 by a combination of black isolated points
PSp and positive type line-shaped regions REp and a character line region
determined in step S25 by a combination of white isolated points PSn and
negative type line-shaped regions REn, (in other words, the OR region of
the two regions (union region)) are finally determined to be a "character
line region".

[0133] According to the processes such as those described above, in steps
S13 and S23, pseudo isolated points are appropriately removed from
line-shaped regions RE which are character line candidate regions. For
example, as shown in FIG. 28, pseudo isolated points can be removed from
the L-shaped "character line region". Then, in steps S14 and S24, a
region from which pseudo isolated points are removed and which includes
only true isolated points is appropriately determined to be a
halftone-dot region. Hence, halftone-dot regions can be more
appropriately extracted from an image containing both characters and
halftone dots.

[0134] Therefore, when a smoothing process is performed on halftone-dot
regions, the smoothing process is not performed on a character line
region RL. Accordingly, the problem of a blurred character edge is
avoided.

[0135] In steps S15 and S25, of true isolated points and pseudo isolated
points, only the true isolated points are appropriately removed from
line-shaped regions RE which are character line candidate regions. For
example, as shown in FIG. 28, a region from which true isolated points
present outside the L-shaped "character line region" are removed is
appropriately determined to be a character line region. Hence, a
character line region can be more appropriately extracted from an image
containing both characters and halftone dots.

[0136] <3. Variants, Etc.>

[0137] Although the embodiment of the present invention is described
above, the present invention is not limited to the content described
above.

[0138] For example, although in the above-described embodiment, in step
S42 (FIG. 5), a detection target region TD is determined to be a region
having, on each side from a pixel of interest EB, a size in the range of
the number of pixels which is the same as an isolated point size N, the
present invention is not limited thereto. Specifically, a detection
target region TD may be determined to be a region having a size in the
range of the number of pixels (N+α) on each side from a pixel of
interest EB. The value α is, for example, one pixel to several
pixels. Alternatively, the value α may be a negative value (e.g.,
-one pixel to-several pixels).

[0139] Although in the above-described embodiment the case is exemplified
in which discontinuity of a line-shaped region in two sets of two
perpendicular directions (DR1 and DR2) and (DR3 and DR4) is determined,
the present invention is not limited thereto, and discontinuity of a
line-shaped region in other perpendicular directions (DR5 and DR6) may be
determined. For example, a direction having an inclination angle of 30
degrees with respect to the X-axis and a direction having an inclination
angle of 120 degrees (-60 degrees) with respect to the X-axis may be
adopted as DR5 and DR6, respectively.

[0140] When a halftone-dot direction is known in advance, it is preferable
to determine discontinuity of a line-shaped region in two perpendicular
directions which are rotated by 45 degrees from the halftone-dot
direction. For example, when it is known that the halftone-dot angle is
45 degrees, it is preferable to determine whether discontinuity of a
line-shaped region is detected on both sides of a pixel of interest EB in
two directions, a direction DR2 having an inclination angle of 90 degrees
with respect to the X-axis and a direction DR1 having an inclination
angle of 0 degrees with respect to the X-axis. Note that a halftone-dot
direction may be detected by performing, for example, a process using a
plurality of filters (linear direction detection filters) for pixel array
detection for different specific directions (e.g., 0 degrees, 45 degrees,
90 degrees, and 135 degrees), on an image resulting from isolated point
detection results (see FIG. 10) obtained in step S11, etc. For each
direction detection filter, for example, an image processing filter of a
predetermined size may be used in which "1" pixels are arranged only in
positions in a corresponding detection direction (e.g., 45 degrees) from
the center and "0" pixels are arranged in other positions. Then, a
specific direction for a direction detection filter with which the
largest computation result (an average value, etc.) is obtained may be
determined to be the halftone-dot direction.

[0141] In particular, when a halftone-dot direction is known in advance,
discontinuity of a line-shaped region only in two directions which are
rotated by 45 degrees from the halftone-dot direction may be determined.
For example, when it is known that the halftone-dot angle is 45 degrees,
an isolated point type determination operation may be performed by
determining only discontinuity of a line-shaped region in the
above-described two perpendicular directions (DR1 and DR2). According to
this, processing efficiency can be achieved.

[0142] Although in the above-described embodiment the case is exemplified
in which an isolated point type is determined according to whether
discontinuity of a line-shaped region is detected on both sides of a
pixel of interest EB in both of two perpendicular directions (e.g., (DR1
and DR2)), the present invention is not limited thereto.

[0143] Specifically, an isolated point type may be determined according to
whether discontinuity of a line-shaped region is detected on both sides
of a pixel of interest EB in at least one of a plurality of directions
(e.g., the above-described four directions DR1 to DR4). More
specifically, when a condition is satisfied where discontinuity of a
line-shaped region is detected on both sides of a pixel of interest EB in
at least one of a plurality of different directions (DR1 to DR4, etc.),
an isolated point associated with the pixel of interest EB may be
determined to be a "true isolated point". On the other hand, when the
condition is not satisfied, the isolated point associated with the pixel
of interest EB may be determined to be a "pseudo isolated point".

[0144] FIG. 29 is a diagram showing a state in which pseudo isolated
points thus determined are removed. As shown in FIG. 29, by a
determination process, etc., according to such a variant, too, pseudo
isolated points in line-shaped regions RE (in particular, a character
line region RL) can be favorably removed. Note that comparing with FIG.
28, in FIG. 29, relatively many isolated points remain in halftone-dot
regions (regions surrounded by dash-dotted lines) and thus it can be seen
that in the variant the condition for determining an isolated point to be
a true isolated point is loosened over that in the above-described
embodiment.

[0145] Although in the above-described embodiment the case of performing
two processes, the process in steps S11 to S15 and the process in steps
S21 to S25, is exemplified, the present invention is not limited thereto
and only one of the two processes may be performed. For example, of the
two processes, only the process in steps S11 to S15 may be performed.

[0146] Although in the above-described embodiment the case is exemplified
in which line-shaped regions are extracted by performing an edge
extraction process, etc., on a scanned image in step S12, etc., the
present invention is not limited thereto. For example, positive type
line-shaped regions may be extracted by performing a low luminance region
extraction process, etc., on a scanned image, etc. Likewise, negative
type line-shaped regions may be extracted by performing a high luminance
region extraction process, etc., on a scanned image, etc. Note that at
this time since regions (solid filled regions, etc.) other than character
line regions are excluded, it is further preferable to extract the
above-described line-shaped regions, with regions having an area of a
certain size or more or having a certain thickness or more being
excluded.

[0147] Although in the above-described embodiment a scanned image created
by the image reading unit 2 is exemplified as image data (digital image
data), the present invention is not limited thereto. For example, image
data may be image data for printing (printing image data) sent from an
external device, etc. The printing image data may be generated by a
scanning process or may be generated by predetermined application
software (a word processor, a graphics processor, etc.).

[0148] Although in the above-described embodiment the case in which the
MFP 1 functions as an image processing apparatus is exemplified, the
present invention is not limited thereto, and a computer (a personal
computer, etc.) may function as an image processing apparatus.

[0149] FIG. 30 is a schematic diagram showing an image processing
apparatus 1 (1B) according to such a variant. The image processing
apparatus 1 (1B) is configured by a computer such as a personal computer.
To the image processing apparatus 1B, a scanned image created by a
scanner apparatus 80 is inputted.

[0150] The image processing apparatus (computer) 1B performs image
processing such as that described above, on the scanned image.
Specifically, the image processing apparatus (computer) 1B reads, from
various types of non-transitory (or portable) computer-readable recording
media 91 (e.g., a flexible disk, a CD-ROM, a DVD-ROM, etc.) having
recorded therein a predetermined program PG, the program PG and executes
the program PG using its CPU, etc., and thereby implements the same
functions as those of the above-described controller 9. Accordingly, the
image processing apparatus (computer) 1B can perform the same image
processing, etc., as those in the above-described embodiment. Note that
the program PG may be supplied through a recording medium or may be
supplied, for example, by being downloaded over the Internet.

[0151] While the invention has been shown and described in detail, the
foregoing description is in all aspects illustrative and not restrictive.
It is therefore understood that numerous modifications and variations can
be devised without departing from the scope of the invention.